Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely
recognized that realistic sensor simulation will play a critical role in solving remaining corner …

We consider the problem of Embodied Question Answering (EQA), which refers to settings
where an embodied agent such as a robot needs to actively explore an environment to …

Object anomaly detection is an important problem in the field of machine vision and has
seen remarkable progress recently. However, two significant challenges hinder its research …

Autonomous vehicles are gradually entering city roads today, with the help of high-definition
maps (HDMaps). However, the reliance on HDMaps prevents autonomous vehicles from …

In this paper, we study multi-target domain adaptation of scene understanding models.
While previous methods achieved commendable results through inter-domain consistency …

Fairness is an important topic for medical image analysis, driven by the challenge of
unbalanced training data among diverse target groups and the societal demand for …

With the success of 2D diffusion models, 2D AIGC content has already transformed our lives.
Recently, this success has been extended to 3D AIGC, with state-of-the-art methods …

End-to-end architectures in autonomous driving (AD) face a significant challenge in
interpretability, impeding human-AI trust. Human-friendly natural language has been …

A simple method is presented for road scene anomaly detection, which is particularly
important in autonomous driving. Without the prior knowledge about the appearance and …

Dealing with atypical traffic scenarios remains a challenging task in autonomous driving.
However, most anomaly detection approaches cannot be trained on raw sensor data but …